When Less Is More: Non-monotonic Spike Sequence Processing in Neurons

Fundamental response properties of neurons centrally underly the computational capabilities of both individual nerve cells and neural networks. Most studies on neuronal input-output relations have focused on continuous-time inputs such as constant or noisy sinusoidal currents. Yet, most neurons communicate via exchanging action potentials (spikes) at discrete times. Here, we systematically analyze the stationary spiking response to regular spiking inputs and reveal that it is generically non-monotonic. Our theoretical analysis shows that the underlying mechanism relies solely on a combination of the discrete nature of the communication by spikes, the capability of locking output to input spikes and limited resources required for spike processing. Numerical simulations of mathematically idealized and biophysically detailed models, as well as neurophysiological experiments confirm and illustrate our theoretical predictions.     

Learning and Exposure Affect Environmental Perception Less than Evolutionary Navigation Costs

Most behaviors are conditional upon successful navigation of the environment, which depends upon distance perception learned over repeated trials. Unfortunately, we understand little about how learning affects distance perception–especially in the most common human navigational scenario, that of adult navigation in familiar environments. Further, dominant theories predict mutually exclusive effects of learning on distance perception, especially when the risks or costs of navigation differ. We tested these competing predictions in four experiments in which we also presented evolutionarily relevant navigation costs. Methods included within- and between-subjects comparisons and longitudinal designs in laboratory and real-world settings. Data suggested that adult distance estimation rapidly reflects evolutionarily relevant navigation costs and repeated exposure does little to change this. Human distance perception may have evolved to reflect navigation costs quickly and reliably in order to provide a stable signal to other behaviors and with little regard for objective accuracy.     

Less Is More: Unveiling the Functional Core of Hematopoietic Stem Cells through Knockout Mice

Hematopoietic stem cells (HSCs) represent one of the first recognized somatic stem cell types. As such, nearly 200 genes have been examined for roles in HSC function in knockout mice. In this review, we compile the majority of these reports to provide a broad overview of the functional modules revealed by these genetic analyses and highlight some key regulatory pathways involved, including cell cycle control, Tgf-β signaling, Pten/Akt signaling, Wnt signaling, and cytokine signaling. Finally, we propose recommendations for characterization of HSC function in knockout mice to facilitate cross-study comparisons that would generate?a more cohesive picture of HSC biology.     

Less Is More: Neisseria gonorrhoeae RecX Protein Stimulates Recombination by Inhibiting RecA

Escherichia coli RecX (RecX_Ec) is a negative regulator of RecA activities both in the bacterial cell and in vitro. In contrast, the Neisseria gonorrhoeae RecX protein (RecX_Ng) enhances all RecA-related processes in N. gonorrhoeae. Surprisingly, the RecX_Ng protein is not a RecA protein activator in vitro. Instead, RecX_Ng is a much more potent inhibitor of all RecA_Ng and RecA_Ec activities than is the E. coli RecX ortholog. A series of RecX_Ng mutant proteins representing a gradient of functional deficiencies provide a direct correlation between RecA_Ng inhibition in vitro and the enhancement of RecA_Ng function in N. gonorrhoeae. Unlike RecX_Ec, RecX_Ng does not simply cap the growing ends of RecA filaments, but it directly facilitates a more rapid RecA filament disassembly. Thus, in N. gonorrhoeae, recombinational processes are facilitated by RecX_Ng protein-mediated limitations on RecA_Ng filament presence and/or length to achieve maximal function.     

When More Transmission Equals Less Disease: Reconciling the Disconnect between Disease Hotspots and Parasite Transmission

The assumed straightforward connection between transmission intensity and disease occurrence impacts surveillance and control efforts along with statistical methodology, including parameter inference and niche modeling. Many infectious disease systems have the potential for this connection to be more complicated–although demonstrating this in any given disease system has remained elusive. Hemorrhagic disease (HD) is one of the most important diseases of white-tailed deer and is caused by viruses in the Orbivirus genus. Like many infectious diseases, the probability or severity of disease increases with age (after loss of maternal antibodies) and the probability of disease is lower upon re-infection compared to first infection (based on cross-immunity between virus strains). These broad criteria generate a prediction that disease occurrence is maximized at intermediate levels of transmission intensity. Using published US field data, we first fit a statistical model to predict disease occurrence as a function of seroprevalence (a proxy for transmission intensity), demonstrating that states with intermediate seroprevalence have the highest level of case reporting. We subsequently introduce an independently parameterized mechanistic model supporting the theory that high case reporting should come from areas with intermediate levels of transmission. This is the first rigorous demonstration of this phenomenon and illustrates that variation in transmission rate (e.g. along an ecologically-controlled transmission gradient) can create cryptic refuges for infectious diseases.     

The Evolutionary Origins of Hierarchy

Hierarchical organization—the recursive composition of sub-modules—is ubiquitous in biological networks, including neural, metabolic, ecological, and genetic regulatory networks, and in human-made systems, such as large organizations and the Internet. To date, most research on hierarchy in networks has been limited to quantifying this property. However, an open, important question in evolutionary biology is why hierarchical organization evolves in the first place. It has recently been shown that modularity evolves because of the presence of a cost for network connections. Here we investigate whether such connection costs also tend to cause a hierarchical organization of such modules. In computational simulations, we find that networks without a connection cost do not evolve to be hierarchical, even when the task has a hierarchical structure. However, with a connection cost, networks evolve to be both modular and hierarchical, and these networks exhibit higher overall performance and evolvability (i.e. faster adaptation to new environments). Additional analyses confirm that hierarchy independently improves adaptability after controlling for modularity. Overall, our results suggest that the same force–the cost of connections–promotes the evolution of both hierarchy and modularity, and that these properties are important drivers of network performance and adaptability. In addition to shedding light on the emergence of hierarchy across the many domains in which it appears, these findings will also accelerate future research into evolving more complex, intelligent computational brains in the fields of artificial intelligence and robotics.     

Patchy Distributions of Competitors Affect the Growth of a Clonal Plant When the Competitor Density Is High

Environments are patchy in not only abiotic factors but also biotic ones. Many studies have examined effects of spatial heterogeneity in abiotic factors such as light, water and nutrients on the growth of clonal plants, but few have tested those in biotic factors. We conducted a greenhouse experiment to examine how patchy distributions of competitors affect the growth of a rhizomatous wetland plant Bolboschoenus planiculmis and whether such effects depend on the density of the competitors. We grew one ramet of B. planiculmis in the center of each of the experimental boxes without competitors (Schoenoplectus triqueter), with a homogeneous distribution of the competitors of low or high density, and with a patchy distribution of the competitors of low or high density. The presence of competitors markedly decreased the growth (biomass, number of ramets, number of tubers and rhizome length) of the B. planiculmis clones. When the density of the competitors was low, the growth of B. planiculmis did not differ significantly between the competitor patches and competitor-free patches. However, when the density of the competitors was high, the growth of B. planiculmis was significantly higher in the competitor-free patches than in the competitor patches. Therefore, B. planiculmis can respond to patchy distributions of competitors by placing more ramets in competition-free patches when the density of competitors is high, but cannot do so when the density of competitors is low.     

Smaller Fixation Target Size Is Associated with More Stable Fixation and Less Variance in Threshold Sensitivity

The aims of this randomized observational case control study were to quantify fixation behavior during standard automated perimetry (SAP) with different fixation targets and to evaluate the relationship between fixation behavior and threshold variability at each test point in healthy young participants experienced with perimetry. SAP was performed on the right eyes of 29 participants using the Octopus 900 perimeter, program 32, dynamic strategy. The fixation targets of Point, Cross, and Ring were used for SAP. Fixation behavior was recorded using a wearable eye-tracking glass. All participants underwent SAP twice with each fixation target in a random fashion. Fixation behavior was quantified by calculating the bivariate contour ellipse area (BCEA) and the frequency of deviation from the fixation target. The BCEAs (deg²) of Point, Cross, and Ring targets were 1.11, 1.46, and 2.02, respectively. In all cases, BCEA increased significantly with increasing fixation target size (p < 0.05). The logarithmic value of BCEA demonstrated the same tendency (p < 0.05). A positive correlation was identified between fixation behavior and threshold variability for the Point and Cross targets (ρ = 0.413–0.534, p < 0.05). Fixation behavior increased with increasing fixation target size. Moreover, a larger fixation behavior tended to be associated with a higher threshold variability. A small fixation target is recommended during the visual field test.